BIT is an experiment in using spatially placed images projected though cubical volume to derive form. The concept is simple, cross and mine the interpolated greyscale values through the use of cubic voxels in a three-axis gradated color space. Use residual values to find form, assign relative color and visualize the data. The goal is surprise and discovery through a process of play and intuition. Taking advantage of Grasshopper for Rhino’s fast-paced dashboard production and easy access to image sampling, along with its ability to use quickly generate color data, the production and use of an easy tool/ toy made the ability to follow intuition in the discovery process fast and clear.
BIT uses volumetric pixel samples from a combination of 6 images cubically arranged. Each tested point acquires its first value from a unitized increment taken between two images arranged across the cube from one another. These two images are then sampled to create a volumetric gradation of values. From these values which represent a low and high greyscale, the function samples linear gradient at a set range of numbers. This returns a unitized value between zero and one which can be converted to any function from the rotation to scaling to color to culling. This process is then repeated for all three pairs of faces, called front, right, and top, which is reflexive to the back, left, and bottom. Crossing sets of these three oriented numbers, a spatial point, returns three values which are summed and divided by 3, giving the average value at a given volumetric point. The use of the three pairs of faces is then used to drive RGB values through the volume. The sample value from each aligned face determines the weight of the sample. The cross of these three results in a smooth transition of colors through the volumes, representing the weight of each sample point in the volume. A cut off threshold is then applied to each volumetric points associated value. When a simple boolean process is applied, the resultant carving of the volume, reflects the weight or density of the sampled values. The forms that remain are residual images of the volumetric crossing of images. The mapping of these volumes onto a planar sampling gives a better sense of the relationship between the color, form and the volume. Other transformation processes can be applied based on the data to better understand the spatial formations within the volumetric crossing of values. Each differentiated spatial placement of the images creates a unique texture, form, and association. BIT is a simple and ongoing exploration both of the potential to derive know forms through a unique process and to discover unknown and unexpected objects through play and intuition.